Which is better, Gemini 3 Pro or GPT-5?

Across 60 shared benchmarks tracked on Vector Wire, Gemini 3 Pro leads on 51 and GPT-5 leads on 9 — Gemini 3 Pro leads on more. Strengths differ by axis; the table below shows every head-to-head number with provenance.

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Gemini 3 Pro vs GPT-5

GooglevsOpenAI60 shared benchmarks51–9 head-to-head

Benchmark	Gemini 3 Pro	GPT-5
AA Agentic Index	52	49.7
AA Intelligence	40.6	35.3
AA-LCR	73	76.3
AA-Omniscience	15.3	-8.7
AIME 2025	100	95
AIME25 no tools	96	94.6
arc_agi_1	75	56.2
ARC-AGI-2	54	7.5
arena_vision	1290	1212
Arena-Hard (Creative Writing)	93.6	92.2
Arena-Hard (Hard Prompt)	72.6	71.9
Artificial Analysis Coding Index	46.5	38.9
browsecomp	59.2	54.9
browsecomp_zh	66.8	65
coding_arena_elo	1438	1419
critpt	9.1	5.7
Fortress	41.7	17
frontiermath_tier_4	18.8	12.5
gdpval	34.2	32.5
GPQA Diamond	91.9	87.3
HLE	45.8	28.5
HLE (with tools)	45.8	35.2
hmmt_feb_2025	97.5	88.3
hmmt_nov_2025	93.3	89.2
IFBench	70.4	73.1
imo_answer_bench	83.3	76
LiveCodeBench	92	85
LiveCodeBench v6	90.7	87
matharena_visual_math_overall	84.2	78.8
metr_hcast	71.3	68.4
metr_re_bench	35	40
metr_swaa	99.5	100
MMLU-Pro	90.1	87.5
MMMU-Pro	81	78.4
Multi-SWE-Bench	42.7	39.3
multichallenge	65.7	71.1
MultiNRC	59	52.1
ocrbench_v2	63.4	55.5
OJ-Bench (cpp)	68.5	56.2
OmniScience Accuracy	55.8	40.3
OmniScience Non-Hallucination	10	21
scicode	56.1	43
SEAL VISTA	51.5	49.7
Seal-0	45.5	51.4
simplebench	76.4	56.7
simpleqa_verified	72.9	50.6
swe_bench_bash	74.2	65
SWE-bench Multilingual	68.7	55.3
SWE-bench Pro	43.3	41.8
SWE-bench Verified	78	74.9
Terminal-Bench 2.0	54.2	35.2
Terminal-Bench Hard	56.9	37.9
vectara_answer_rate	99.4	99.9
vectara_avg_summary_length	101.9	162.7
vectara_factual_consistency	86.4	85.3
vectara_hallucination_rate ↓	13.6	14.7
VideoMMMU	87.6	84.6
VisualToolBench	26.9	18.7
τ²-Bench	98	85
τ²-Bench Telecom (AA run)	98	86.5

Best tracked score per model per benchmark (default configuration; source-attributed). ↓ marks lower-is-better metrics. Open either model for its full surface, provenance and pricing.